Pub Date : 2025-10-24DOI: 10.1109/OJIES.2025.3625471
Reza Behnam;Uzair Asif;Mohammad B. Shadmand
For the integration of distributed energy resources into the power grid, grid-forming inverters (GFMIs) play a key role due to their voltage support capability. However, the low-inertia inverter-based generation can pose stability challenges to the power system. One of the major challenges is the dynamic behavior of GFMIs when subjected to disturbances and irregularities, including disturbances in dc link voltage. Most of the existing studies do not consider the dc link voltage variations for GFMIs, overlooking the impact of their sudden fluctuations on the system performance. This article proposes a decentralized control approach that uses a neural network-based method to dynamically adjust the inertia and damping coefficient of the virtual synchronous generator in real time for improving the dynamic response of GFMIs to dc link voltage disturbances. The effectiveness of the proposed approach is validated through various case studies on a 9-bus, four-GFMI test system in MATLAB/Simulink. Furthermore, experimental hardware results also validate the effectiveness of the proposed approach.
{"title":"AI-Based Control Scheme for Resilient Grid-Forming Inverters Under DC Link Voltage Disturbances","authors":"Reza Behnam;Uzair Asif;Mohammad B. Shadmand","doi":"10.1109/OJIES.2025.3625471","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3625471","url":null,"abstract":"For the integration of distributed energy resources into the power grid, grid-forming inverters (GFMIs) play a key role due to their voltage support capability. However, the low-inertia inverter-based generation can pose stability challenges to the power system. One of the major challenges is the dynamic behavior of GFMIs when subjected to disturbances and irregularities, including disturbances in dc link voltage. Most of the existing studies do not consider the dc link voltage variations for GFMIs, overlooking the impact of their sudden fluctuations on the system performance. This article proposes a decentralized control approach that uses a neural network-based method to dynamically adjust the inertia and damping coefficient of the virtual synchronous generator in real time for improving the dynamic response of GFMIs to dc link voltage disturbances. The effectiveness of the proposed approach is validated through various case studies on a 9-bus, four-GFMI test system in MATLAB/Simulink. Furthermore, experimental hardware results also validate the effectiveness of the proposed approach.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1743-1755"},"PeriodicalIF":4.3,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11216347","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-22DOI: 10.1109/OJIES.2025.3624462
Muntathir Al Talaq;Muhammad Bakr Abdelghany;Ahmed Al-Durra;Hatem H. Zeineldin;Tarek H. M. EL-Fouly
The increasing penetration of inverter-based renewable energy sources (IBRs), such as wind turbines and photovoltaic systems, offers an environmentally sustainable and cost-effective solution for achieving net-zero emissions. However, integrating these systems into power grids poses significant challenges in maintaining a reliable power supply, particularly due to the operational characteristics of IBRs. IBR control strategies are typically classified into two configurations: GFM and grid-following control (GFL). This article proposes a novel optimization framework for the strategic allocation of IBRs and the selection of their control configurations, ensuring both cost-effective placement and system stability. A two-stage optimization approach is employed: the first stage optimizes IBR placement, quantity, and dispatched power to minimize total power losses and enhance network efficiency, while the second stage determines the optimal inverter configuration to improve dynamic stability, supporting the development of resilient and decarbonized energy networks. The proposed methodology is validated on a modified IEEE 38-bus system, representing a future grid scenario with a high share of IBRs. The results indicate that the GFM inverters should be connected to the main feeder connected to the weak grid, whereas the GFL inverters are best suited for branch feeders. Furthermore, the optimal placement of the GFM inverters is influenced by the network topology and loading conditions, highlighting the adaptability of the proposed framework to varying grid configurations.
{"title":"Optimal Configuration and Coordinated Scheduling of Hybrid Inverter-Based Energy Sources in Large-Scale Green Management Systems","authors":"Muntathir Al Talaq;Muhammad Bakr Abdelghany;Ahmed Al-Durra;Hatem H. Zeineldin;Tarek H. M. EL-Fouly","doi":"10.1109/OJIES.2025.3624462","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3624462","url":null,"abstract":"The increasing penetration of inverter-based renewable energy sources (IBRs), such as wind turbines and photovoltaic systems, offers an environmentally sustainable and cost-effective solution for achieving net-zero emissions. However, integrating these systems into power grids poses significant challenges in maintaining a reliable power supply, particularly due to the operational characteristics of IBRs. IBR control strategies are typically classified into two configurations: GFM and grid-following control (GFL). This article proposes a novel optimization framework for the strategic allocation of IBRs and the selection of their control configurations, ensuring both cost-effective placement and system stability. A two-stage optimization approach is employed: the first stage optimizes IBR placement, quantity, and dispatched power to minimize total power losses and enhance network efficiency, while the second stage determines the optimal inverter configuration to improve dynamic stability, supporting the development of resilient and decarbonized energy networks. The proposed methodology is validated on a modified IEEE 38-bus system, representing a future grid scenario with a high share of IBRs. The results indicate that the GFM inverters should be connected to the main feeder connected to the weak grid, whereas the GFL inverters are best suited for branch feeders. Furthermore, the optimal placement of the GFM inverters is influenced by the network topology and loading conditions, highlighting the adaptability of the proposed framework to varying grid configurations.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1720-1742"},"PeriodicalIF":4.3,"publicationDate":"2025-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11214244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-20DOI: 10.1109/OJIES.2025.3623250
Vincent Henkel;Lukas Peter Wagner;Maximilian Kilthau;Felix Gehlhoff;Alexander Fay
Effectively utilizing flexible energy resources requires optimizing their operation over time to balance dynamic demand and fluctuating supply from volatile renewable sources. Traditionally, this has been achieved through centralized optimization models, which suffer from scalability limitations, single points of failure, and limited flexibility when applied to decentralized and dynamically changing environments. Distributed models offer a promising alternative, providing enhanced flexibility, robustness, and computational efficiency by enabling parallel processing and reducing coordination delays. Thus, this work presents a methodology for the semi-automated transformation of centralized optimization models into distributed architectures, leveraging containerized multiagent systems to achieve scalable and efficient optimization across multiple computing units. A case study involving 120 electrolyzers distributed across up to five optimization agents, including both homogeneous and heterogeneous configurations, demonstrates that the distributed approach accelerates computation time by a factor up to 27.42 compared to a centralized model while accepting a solution quality deviation of only 2.2%. The optimization integrates site-wide and real-time optimization, ensuring adaptability to fluctuating renewable energy availability and improving system resilience. This combination enables long-term strategic planning while allowing real-time adjustments to maximize renewable energy utilization. The findings highlight the benefits of distributed optimization in modular energy systems and confirm that containerized multiagent architectures enhance scalability and computational efficiency, making the approach well-suited for real-world applications in decentralized and modular energy networks.
{"title":"Methodology for Distributed Optimization of Flexible Energy Resources Through Semi-Automated Model Transformation and Deployment","authors":"Vincent Henkel;Lukas Peter Wagner;Maximilian Kilthau;Felix Gehlhoff;Alexander Fay","doi":"10.1109/OJIES.2025.3623250","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3623250","url":null,"abstract":"Effectively utilizing flexible energy resources requires optimizing their operation over time to balance dynamic demand and fluctuating supply from volatile renewable sources. Traditionally, this has been achieved through centralized optimization models, which suffer from scalability limitations, single points of failure, and limited flexibility when applied to decentralized and dynamically changing environments. Distributed models offer a promising alternative, providing enhanced flexibility, robustness, and computational efficiency by enabling parallel processing and reducing coordination delays. Thus, this work presents a methodology for the semi-automated transformation of centralized optimization models into distributed architectures, leveraging containerized multiagent systems to achieve scalable and efficient optimization across multiple computing units. A case study involving 120 electrolyzers distributed across up to five optimization agents, including both homogeneous and heterogeneous configurations, demonstrates that the distributed approach accelerates computation time by a factor up to 27.42 compared to a centralized model while accepting a solution quality deviation of only 2.2%. The optimization integrates site-wide and real-time optimization, ensuring adaptability to fluctuating renewable energy availability and improving system resilience. This combination enables long-term strategic planning while allowing real-time adjustments to maximize renewable energy utilization. The findings highlight the benefits of distributed optimization in modular energy systems and confirm that containerized multiagent architectures enhance scalability and computational efficiency, making the approach well-suited for real-world applications in decentralized and modular energy networks.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1682-1703"},"PeriodicalIF":4.3,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11207504","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Virtual power plants (VPPs) have emerged as critical infrastructure for grid stability, aggregating diverse Distributed energy resources (DERs) to provide essential ancillary services, including frequency regulation, voltage support, and emergency response capabilities. However, the technical requirements that enable VPPs to deliver these time-critical services simultaneously create unique cybersecurity vulnerabilities that distinguish them from traditional power generation and conventional smart grid systems. This article establishes systematic connections between VPP technical requirements and cybersecurity threats through the integrated application of NIST and MITRE frameworks. The objective is to reveal critical threats specifically pertaining to ancillary services, comprehensive attack vector classification using MITRE ATT&CK techniques adapted for VPP environments, and mitigation strategies that maintain operational performance while addressing identified vulnerabilities.
{"title":"Securing Virtual Power Plants: Attack Vector Analysis of Cybersecurity Vulnerabilities in Ancillary Grid Services","authors":"Afroz Mokarim;Giovanni Battista Gaggero;Mario Marchese","doi":"10.1109/OJIES.2025.3622528","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3622528","url":null,"abstract":"Virtual power plants (VPPs) have emerged as critical infrastructure for grid stability, aggregating diverse Distributed energy resources (DERs) to provide essential ancillary services, including frequency regulation, voltage support, and emergency response capabilities. However, the technical requirements that enable VPPs to deliver these time-critical services simultaneously create unique cybersecurity vulnerabilities that distinguish them from traditional power generation and conventional smart grid systems. This article establishes systematic connections between VPP technical requirements and cybersecurity threats through the integrated application of NIST and MITRE frameworks. The objective is to reveal critical threats specifically pertaining to ancillary services, comprehensive attack vector classification using MITRE ATT&CK techniques adapted for VPP environments, and mitigation strategies that maintain operational performance while addressing identified vulnerabilities.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1704-1719"},"PeriodicalIF":4.3,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11205291","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-14DOI: 10.1109/OJIES.2025.3621471
Mohammad Qasem;Yazan Yassin;Mariana Haddadin;Stoyan Stoyanov;Said Al-Hallaj;Mahesh Krishnamurthy
Conventional fast-charging methods for lithium-ion batteries (LIBs) face challenges in balancing charging speed, adverse side reactions, and battery degradation. This research introduces a novel dynamic fast-charging control approach incorporated into an age-aware battery management system. The proposed system utilizes a simplified electrochemical model and integrates closed-loop observers to detect lithium plating and solid electrolyte interphase (SEI) growth, allowing real-time updates to charging profiles depending on battery states such as the state of charge (SoC), state of health, and temperature. Experimental validation is conducted using NMC811 LIB cells arranged in a 4S9P pack configuration at ambient temperatures of 25 $^{circ }$C and 0 $^{circ }$C to meet the operational requirements of electric vertical take-off and landing (eVTOL) applications. The results indicate that the dynamic fast-charging controller achieves an 80% SoC in less than 28 min while avoiding lithium plating and excessive SEI growth, enhancing battery longevity by 25.2% and 8.8% compared to constant-current–constant-voltage (CC–CV) and multi-constant current (MCC)–CV, respectively, and reducing internal impedance growth by 45% and 15%. These enhancements ensure safe operation and consistent performance in high-power, low-temperature conditions, where traditional techniques often fail. This study highlights the feasibility of the dynamic charging technique for real-world applications, improving economic efficiency and reliability in eVTOL operations.
{"title":"Dynamic Fast-Charging Control With Age-Aware BMS for Enhanced Safety and Efficiency in Li-ion Batteries","authors":"Mohammad Qasem;Yazan Yassin;Mariana Haddadin;Stoyan Stoyanov;Said Al-Hallaj;Mahesh Krishnamurthy","doi":"10.1109/OJIES.2025.3621471","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3621471","url":null,"abstract":"Conventional fast-charging methods for lithium-ion batteries (LIBs) face challenges in balancing charging speed, adverse side reactions, and battery degradation. This research introduces a novel dynamic fast-charging control approach incorporated into an age-aware battery management system. The proposed system utilizes a simplified electrochemical model and integrates closed-loop observers to detect lithium plating and solid electrolyte interphase (SEI) growth, allowing real-time updates to charging profiles depending on battery states such as the state of charge (SoC), state of health, and temperature. Experimental validation is conducted using NMC811 LIB cells arranged in a 4S9P pack configuration at ambient temperatures of 25 <inline-formula><tex-math>$^{circ }$</tex-math></inline-formula>C and 0 <inline-formula><tex-math>$^{circ }$</tex-math></inline-formula>C to meet the operational requirements of electric vertical take-off and landing (eVTOL) applications. The results indicate that the dynamic fast-charging controller achieves an 80% SoC in less than 28 min while avoiding lithium plating and excessive SEI growth, enhancing battery longevity by 25.2% and 8.8% compared to constant-current–constant-voltage (CC–CV) and multi-constant current (MCC)–CV, respectively, and reducing internal impedance growth by 45% and 15%. These enhancements ensure safe operation and consistent performance in high-power, low-temperature conditions, where traditional techniques often fail. This study highlights the feasibility of the dynamic charging technique for real-world applications, improving economic efficiency and reliability in eVTOL operations.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1663-1681"},"PeriodicalIF":4.3,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11202713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article presents a new high-voltage-gain, common-ground power factor correction (PFC) active rectifier. The proposed power converter offers several advantages, including a quadratic voltage gain ratio that surpasses both common-ground and noncommon-ground buck–boost PFC converters. It also incorporates an integrated active power decoupling method to reduce the size of the dc-link capacitor. The design ensures continuous input current for high-quality input power, while utilizing only five switches. With a common ground between the input ac source and the output dc load, the converter effectively mitigates electromagnetic interference (EMI) associated with rapid voltage changes, thereby reducing the need for EMI common-mode filtering. Furthermore, a new two-loop deadbeat control system is introduced to efficiently regulate both the inner and outer control loops. Experimental results from a 500 W prototype validate the rectifier’s performance in both step-down and step-up ac–dc power conversion. Operating from a 110 Vrms input, the prototype achieves 80 Vdc and 180 Vdc outputs, with peak efficiencies of 97.0% and 96.9%, respectively.
{"title":"A Common Ground Buck–Boost PFC Converter With Quadratic Voltage Gain Ratio and Integrated Active Power Decoupling Capabilities","authors":"Maryam Pourmahdi;Hamed Heydari-Doostabad;Terence O’Donnell","doi":"10.1109/OJIES.2025.3621244","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3621244","url":null,"abstract":"This article presents a new high-voltage-gain, common-ground power factor correction (PFC) active rectifier. The proposed power converter offers several advantages, including a quadratic voltage gain ratio that surpasses both common-ground and noncommon-ground buck–boost PFC converters. It also incorporates an integrated active power decoupling method to reduce the size of the dc-link capacitor. The design ensures continuous input current for high-quality input power, while utilizing only five switches. With a common ground between the input ac source and the output dc load, the converter effectively mitigates electromagnetic interference (EMI) associated with rapid voltage changes, thereby reducing the need for EMI common-mode filtering. Furthermore, a new two-loop deadbeat control system is introduced to efficiently regulate both the inner and outer control loops. Experimental results from a 500 W prototype validate the rectifier’s performance in both step-down and step-up ac–dc power conversion. Operating from a 110 Vrms input, the prototype achieves 80 Vdc and 180 Vdc outputs, with peak efficiencies of 97.0% and 96.9%, respectively.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1629-1649"},"PeriodicalIF":4.3,"publicationDate":"2025-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11202716","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-13DOI: 10.1109/OJIES.2025.3620857
Marco Stella;Antonio Faba;Vittorio Bertolini;Francesco Riganti-Fulginei;Lorenzo Sabino;Hans Tiismus;Ants Kallaste;Ermanno Cardelli
Presently, iron–silicon (Fe–Si) alloys are considered the optimal materials for the fabrication of magnetic cores for electric motors. Additive manufacturing (AM) facilitates the fabrication of Fe–Si alloys with elevated silicon concentrations, highly advantageous to limit the electric conductivity and maximize the magnetic permeability. Given the novelty of the approach, there is a paucity of research on hysteresis modeling and simulations of components fabricated by AM. In this article, the focus is on a Fe–Si 3.7% wt Si fabricated by AM. The hysteresis has been modeled by means of an artificial neural network (ANN) trained on the quasi-static (1 Hz) hysteresis loops measured using the volt-amperometric experimental setup on the bulk material, a full-section toroid. The trained ANN is subsequently implemented in a finite-element method (FEM) software to simulate the hysteresis on a material sample with air gaps and at higher frequencies never seen in the training phase. This work demonstrates, for the first time, the robust predictive capability of an ANN–FEM framework. A key contribution is the validation of the model under purely predictive conditions, using a geometry and frequency range entirely unseen during training. The simulated results have been compared with measurements and with results obtained with the classical Jiles–Atherton (JA) model. The correlation between the ANN results and the experimental data is substantial, consistent with the JA results, and in certain instances, superior.
{"title":"Modeling of Magnetization Processes of 3-D-Printed Fe–Si Components by Means of an Artificial Neural Network Implemented in a Finite-Element Scheme","authors":"Marco Stella;Antonio Faba;Vittorio Bertolini;Francesco Riganti-Fulginei;Lorenzo Sabino;Hans Tiismus;Ants Kallaste;Ermanno Cardelli","doi":"10.1109/OJIES.2025.3620857","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3620857","url":null,"abstract":"Presently, iron–silicon (Fe–Si) alloys are considered the optimal materials for the fabrication of magnetic cores for electric motors. Additive manufacturing (AM) facilitates the fabrication of Fe–Si alloys with elevated silicon concentrations, highly advantageous to limit the electric conductivity and maximize the magnetic permeability. Given the novelty of the approach, there is a paucity of research on hysteresis modeling and simulations of components fabricated by AM. In this article, the focus is on a Fe–Si 3.7% wt Si fabricated by AM. The hysteresis has been modeled by means of an artificial neural network (ANN) trained on the quasi-static (1 Hz) hysteresis loops measured using the volt-amperometric experimental setup on the bulk material, a full-section toroid. The trained ANN is subsequently implemented in a finite-element method (FEM) software to simulate the hysteresis on a material sample with air gaps and at higher frequencies never seen in the training phase. This work demonstrates, for the first time, the robust predictive capability of an ANN–FEM framework. A key contribution is the validation of the model under purely predictive conditions, using a geometry and frequency range entirely unseen during training. The simulated results have been compared with measurements and with results obtained with the classical Jiles–Atherton (JA) model. The correlation between the ANN results and the experimental data is substantial, consistent with the JA results, and in certain instances, superior.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1650-1662"},"PeriodicalIF":4.3,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11202631","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1109/OJIES.2025.3617573
Aditya Kumar;Shiv Prakash;Sandip Ghosh;N. K. Swami Naidu;Pawel Dworak
This article considers the problem of controller design for a grid-connected wind energy conversion system (WECS) employing a variable-speed permanent magnet synchronous generator (PMSG). The system architecture comprises of two back-to-back converters connecting the PMSG to the grid. The variable-speed control of the PMSG using the machine-side converter employs a multi-input multioutput (MIMO) inner-loop current control. Although there are sophisticated control strategies to address MIMO design requirements, their practical deployment is often hindered by implementation complexity and computational demands for higher order controllers. In contrast, conventional proportional–integral (PI) controllers remain attractive for embedded applications because of their simplicity and easy hardware realizability. However, traditional PI control approaches rely on current-loop decoupling through feedforward compensation and thereby design in the single-input single-output framework, leading to suboptimal performances. To overcome this, a MIMO control design framework is proposed that explicitly considers the coupling in the system model. The controller design employs a two-stage approach: 1) designing the decentralized inner-loop current controllers in a MIMO framework and then 2) the outer-loop speed controller design. The structured PI controller requires the controller to be designed in a static output feedback framework. Simple weight functions in $H_{infty }$ robust control framework are chosen for the current-loop controller design to simplify the output feedback design criterion. While achieving robustness to disturbance rejection, the simultaneous regional pole placement criterion is used to ensure well-damped transient responses. Experiments on a laboratory-scale PMSG-based WECS validate the effectiveness of the proposed control design method that outperforms conventionally designed PI controllers in both transient and steady-state performances.
{"title":"Robust Decentralized PI Controller Design for Permanent Magnet Synchronous Generator","authors":"Aditya Kumar;Shiv Prakash;Sandip Ghosh;N. K. Swami Naidu;Pawel Dworak","doi":"10.1109/OJIES.2025.3617573","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3617573","url":null,"abstract":"This article considers the problem of controller design for a grid-connected wind energy conversion system (WECS) employing a variable-speed permanent magnet synchronous generator (PMSG). The system architecture comprises of two back-to-back converters connecting the PMSG to the grid. The variable-speed control of the PMSG using the machine-side converter employs a multi-input multioutput (MIMO) inner-loop current control. Although there are sophisticated control strategies to address MIMO design requirements, their practical deployment is often hindered by implementation complexity and computational demands for higher order controllers. In contrast, conventional proportional–integral (PI) controllers remain attractive for embedded applications because of their simplicity and easy hardware realizability. However, traditional PI control approaches rely on current-loop decoupling through feedforward compensation and thereby design in the single-input single-output framework, leading to suboptimal performances. To overcome this, a MIMO control design framework is proposed that explicitly considers the coupling in the system model. The controller design employs a two-stage approach: 1) designing the decentralized inner-loop current controllers in a MIMO framework and then 2) the outer-loop speed controller design. The structured PI controller requires the controller to be designed in a static output feedback framework. Simple weight functions in <inline-formula><tex-math>$H_{infty }$</tex-math></inline-formula> robust control framework are chosen for the current-loop controller design to simplify the output feedback design criterion. While achieving robustness to disturbance rejection, the simultaneous regional pole placement criterion is used to ensure well-damped transient responses. Experiments on a laboratory-scale PMSG-based WECS validate the effectiveness of the proposed control design method that outperforms conventionally designed PI controllers in both transient and steady-state performances.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1617-1628"},"PeriodicalIF":4.3,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11192649","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-23DOI: 10.1109/OJIES.2025.3613601
Daniele Martini;Michela Longo;Luca Daniel
The scope of this article is to assess the economic viability of bidirectional charging strategies for scheduled electric bus fleets, focusing on their potential to reduce operational costs under real-world market conditions. This article presents a comprehensive and production-ready optimization framework for vehicle-to-grid integration, addressing day-ahead pricing, battery degradation, and grid constraints through a mixed-integer linear programming formulation. Unlike existing approaches that often rely on aggregated vehicle behavior, our framework preserves the full topology of the charging station, maintaining vehicle-level granularity. This enables precise evaluation of both marginal costs and savings, enhancing the model’s practical relevance and deployment potential. Results from real-world fleet schedules and Italian market data show that both controlled charging and vehicle-to-grid achieve substantially lower costs than uncontrolled charging, with savings exceeding 35% in current scenarios. However, the cost gap between vehicle-to-grid and controlled charging remains narrow. These findings indicate that as battery pack prices continue to decline and energy markets evolve, vehicle-to-grid will become increasingly favorable for scheduled fleets.
{"title":"MILP Framework for V2G Optimization With Battery Degradation and Price Arbitrage in Scheduled Fleets","authors":"Daniele Martini;Michela Longo;Luca Daniel","doi":"10.1109/OJIES.2025.3613601","DOIUrl":"https://doi.org/10.1109/OJIES.2025.3613601","url":null,"abstract":"The scope of this article is to assess the economic viability of bidirectional charging strategies for scheduled electric bus fleets, focusing on their potential to reduce operational costs under real-world market conditions. This article presents a comprehensive and production-ready optimization framework for vehicle-to-grid integration, addressing day-ahead pricing, battery degradation, and grid constraints through a mixed-integer linear programming formulation. Unlike existing approaches that often rely on aggregated vehicle behavior, our framework preserves the full topology of the charging station, maintaining vehicle-level granularity. This enables precise evaluation of both marginal costs and savings, enhancing the model’s practical relevance and deployment potential. Results from real-world fleet schedules and Italian market data show that both controlled charging and vehicle-to-grid achieve substantially lower costs than uncontrolled charging, with savings exceeding 35% in current scenarios. However, the cost gap between vehicle-to-grid and controlled charging remains narrow. These findings indicate that as battery pack prices continue to decline and energy markets evolve, vehicle-to-grid will become increasingly favorable for scheduled fleets.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"6 ","pages":"1593-1602"},"PeriodicalIF":4.3,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11176439","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145210063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1109/OJIES.2025.3610876
Dong Xu;Guanda Yang;Heyang Feng;Xinnuo Wang;Yupeng Liu
With the increasing adoption of robotic manipulators in precision manufacturing and automation, the demand for high efficiency and accuracy has grown significantly. However, these systems often face persistent vibration issues due to their lightweight and flexible structures, which compromise performance. Although there are various studies related to vibration suppression, a comprehensive review of this topic remains absent. This article aims to fill that gap by categorizing recent advances in vibration suppression into passive approaches that use vibration isolators and active approaches that employ closed-loop control systems. Through a critical evaluation of the strengths and limitations of each approach, this review highlights key challenges and emerging trends in the field, offering valuable insights for future research aimed at improving the efficiency and precision of robotic manipulators.
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